Quantitative Assessment of the Impact of Geometric Distortions and Their Correction on fMRI Data Analyses

Detalhes bibliográficos
Autor(a) principal: Abreu, Rodolfo
Data de Publicação: 2021
Outros Autores: Duarte, João Valente
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10316/104548
https://doi.org/10.3389/fnins.2021.642808
Resumo: Functional magnetic resonance imaging (fMRI) data is typically collected with gradient-echo echo-planar imaging (GE-EPI) sequences, which are particularly prone to the susceptibility artifact as a result of B0 field inhomogeneity. The component derived from in-plane spin dephasing induces pixel intensity variations and, more critically, geometric distortions. Despite the physical mechanisms underlying the susceptibility artifact being well established, a systematic investigation on the impact of the associated geometric distortions, and the direct comparison of different approaches to tackle them, on fMRI data analyses is missing. Here, we compared two different distortion correction approaches, by acquiring additional: (1) EPI data with reversed phase encoding direction (TOPUP), and (2) standard (and undistorted) GE data at two different echo times (GRE). We first characterized the geometric distortions and the correction approaches based on the estimated ΔB0 field offset and voxel shift maps, and then conducted three types of analyses on the distorted and corrected fMRI data: (1) registration into structural data, (2) identification of resting-state networks (RSNs), and (3) mapping of task-related brain regions of interest. GRE estimated the largest voxel shifts and more positively impacted the quality of the analyses, in terms of the (significantly lower) cost function of the registration, the (higher) spatial overlap between the RSNs and appropriate templates, and the (significantly higher) sensitivity of the task-related mapping based on the Z-score values of the associated activation maps, although also evident when considering TOPUP. fMRI data should thus be corrected for geometric distortions, with the choice of the approach having a modest, albeit positive, impact on the fMRI analyses.
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spelling Quantitative Assessment of the Impact of Geometric Distortions and Their Correction on fMRI Data AnalysesfMRIsusceptibility artifactgeometric distortions and correctionB0 field mappingneuroimagingFunctional magnetic resonance imaging (fMRI) data is typically collected with gradient-echo echo-planar imaging (GE-EPI) sequences, which are particularly prone to the susceptibility artifact as a result of B0 field inhomogeneity. The component derived from in-plane spin dephasing induces pixel intensity variations and, more critically, geometric distortions. Despite the physical mechanisms underlying the susceptibility artifact being well established, a systematic investigation on the impact of the associated geometric distortions, and the direct comparison of different approaches to tackle them, on fMRI data analyses is missing. Here, we compared two different distortion correction approaches, by acquiring additional: (1) EPI data with reversed phase encoding direction (TOPUP), and (2) standard (and undistorted) GE data at two different echo times (GRE). We first characterized the geometric distortions and the correction approaches based on the estimated ΔB0 field offset and voxel shift maps, and then conducted three types of analyses on the distorted and corrected fMRI data: (1) registration into structural data, (2) identification of resting-state networks (RSNs), and (3) mapping of task-related brain regions of interest. GRE estimated the largest voxel shifts and more positively impacted the quality of the analyses, in terms of the (significantly lower) cost function of the registration, the (higher) spatial overlap between the RSNs and appropriate templates, and the (significantly higher) sensitivity of the task-related mapping based on the Z-score values of the associated activation maps, although also evident when considering TOPUP. fMRI data should thus be corrected for geometric distortions, with the choice of the approach having a modest, albeit positive, impact on the fMRI analyses.PAC–286 MEDPERSYST, POCI-01-0145-FEDER-016428, BIGDATIMAGE, CENTRO- 01-0145-FEDER-000016 financed by Centro 2020 FEDER, COMPETE, FCT UID/4950/2020–COMPETE, CONNECT.BCI POCI-01-0145-FEDER-30852, and BIOMUSCLE PTDC/MECNEU/ 31973/2017–CENTRO-01-0145-FEDER-031973. FCT also funded an individual grant to JD (Individual Scientific Employment Stimulus 2017–CEECIND/00581/2017).Frontiers Media S.A.2021info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10316/104548http://hdl.handle.net/10316/104548https://doi.org/10.3389/fnins.2021.642808eng1662-4548Abreu, RodolfoDuarte, João Valenteinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-04-06T10:20:24Zoai:estudogeral.uc.pt:10316/104548Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T21:21:14.513704Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Quantitative Assessment of the Impact of Geometric Distortions and Their Correction on fMRI Data Analyses
title Quantitative Assessment of the Impact of Geometric Distortions and Their Correction on fMRI Data Analyses
spellingShingle Quantitative Assessment of the Impact of Geometric Distortions and Their Correction on fMRI Data Analyses
Abreu, Rodolfo
fMRI
susceptibility artifact
geometric distortions and correction
B0 field mapping
neuroimaging
title_short Quantitative Assessment of the Impact of Geometric Distortions and Their Correction on fMRI Data Analyses
title_full Quantitative Assessment of the Impact of Geometric Distortions and Their Correction on fMRI Data Analyses
title_fullStr Quantitative Assessment of the Impact of Geometric Distortions and Their Correction on fMRI Data Analyses
title_full_unstemmed Quantitative Assessment of the Impact of Geometric Distortions and Their Correction on fMRI Data Analyses
title_sort Quantitative Assessment of the Impact of Geometric Distortions and Their Correction on fMRI Data Analyses
author Abreu, Rodolfo
author_facet Abreu, Rodolfo
Duarte, João Valente
author_role author
author2 Duarte, João Valente
author2_role author
dc.contributor.author.fl_str_mv Abreu, Rodolfo
Duarte, João Valente
dc.subject.por.fl_str_mv fMRI
susceptibility artifact
geometric distortions and correction
B0 field mapping
neuroimaging
topic fMRI
susceptibility artifact
geometric distortions and correction
B0 field mapping
neuroimaging
description Functional magnetic resonance imaging (fMRI) data is typically collected with gradient-echo echo-planar imaging (GE-EPI) sequences, which are particularly prone to the susceptibility artifact as a result of B0 field inhomogeneity. The component derived from in-plane spin dephasing induces pixel intensity variations and, more critically, geometric distortions. Despite the physical mechanisms underlying the susceptibility artifact being well established, a systematic investigation on the impact of the associated geometric distortions, and the direct comparison of different approaches to tackle them, on fMRI data analyses is missing. Here, we compared two different distortion correction approaches, by acquiring additional: (1) EPI data with reversed phase encoding direction (TOPUP), and (2) standard (and undistorted) GE data at two different echo times (GRE). We first characterized the geometric distortions and the correction approaches based on the estimated ΔB0 field offset and voxel shift maps, and then conducted three types of analyses on the distorted and corrected fMRI data: (1) registration into structural data, (2) identification of resting-state networks (RSNs), and (3) mapping of task-related brain regions of interest. GRE estimated the largest voxel shifts and more positively impacted the quality of the analyses, in terms of the (significantly lower) cost function of the registration, the (higher) spatial overlap between the RSNs and appropriate templates, and the (significantly higher) sensitivity of the task-related mapping based on the Z-score values of the associated activation maps, although also evident when considering TOPUP. fMRI data should thus be corrected for geometric distortions, with the choice of the approach having a modest, albeit positive, impact on the fMRI analyses.
publishDate 2021
dc.date.none.fl_str_mv 2021
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10316/104548
http://hdl.handle.net/10316/104548
https://doi.org/10.3389/fnins.2021.642808
url http://hdl.handle.net/10316/104548
https://doi.org/10.3389/fnins.2021.642808
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language eng
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dc.publisher.none.fl_str_mv Frontiers Media S.A.
publisher.none.fl_str_mv Frontiers Media S.A.
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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